Artificial Intelligence for the analysis of data in agricultural robotics - 2026_IDR_DEIB_29

Position: Research appointment (pre-doc) Institute: Polytechnic of Milano
Posted on: 07/04/2026 Deadline: 15/05/2026

Scientific-Disciplinary Group

09/IINF-05 - Information Processing Systems

Description

The research program focuses on the development of advanced methodologies for data acquisition, integration, and analysis in the field of agricultural robotics. The aim is to investigate techniques capable of handling multimodal data from heterogeneous sensors (e.g., 2D and 3D imagery, environmental sensing data, geospatial signals, and agronomic data), integrating them to generate semantic spatial models in robotic contexts. The purpose of these models is to support applications such as crop monitoring, early anomaly detection (e.g., water stress, diseases, pest infestations), yield prediction, and the optimization of automated agricultural operations. The developed models are expected to effectively leverage metadata to guide decision-making processes and improve the interpretation of data collected by robotic systems. By exploiting contextual and multimodal information, the proposed approaches aim to enhance accuracy and robustness in data analysis.

Job posting website

https://www.polimi.it/en/bandi-incarichidiricerca

Number of positions

1

Funding body

Politecnico di Milano

How to apply

https://aunicalogin.polimi.it/aunicalogin/getservizio.xml?id_servizio=1079

Selection process

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In order to participate in the selection, please read the call ("bando") available at the following website: https://www.polimi.it/en/bandi-incarichidiricerca Oral test aimed at ascertaining candidates’ aptitude and suitability to carry out the research activity covered by the Fellowship, as well as at assessing their knowledge of English and/or other languages relevant to the research activities to be performed (up to 50 points) Relevance and pertinence of the publications, theses and scientific products attached to the research programme covered by the Fellowship (up to 10 points) Relevance and pertinence of previous research activities and work experience, if any, in relation to the research activity covered by the Fellowship (up to 20 points) Relevance and pertinence of their study programme to the research programme covered by the Fellowship (up to 20 points)

View the original posting on the MUR website: Go to MUR website

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